A method to account for diversity of practices in Conservation Agriculture

Author:

Ferdinand Manon S.ORCID,Baret Philippe V.

Abstract

AbstractConservation Agriculture (CA) is actively promoted as an alternative farming system that combines environmental, economic, and social sustainability. Three pillars define CA: (i) minimum mechanical soil disturbance, (ii) permanent soil organic cover, and (iii) species diversification. The local context, constraints, and needs of the farmers influence the translation of the pillars into practices. Currently, there is no method for categorizing this diversity of CA practices, which hampers impact assessment, understanding of farmer choices and pathways, stakeholder communication, and policymaking. This paper presents a systematic method to identify and categorize the diversity of CA practices at the regional level, anchored in the three pillars and based on practices implemented by CA farmers. The classification method is grounded on the intersection of an archetypal analysis and a hierarchical clustering analysis. This method was used to study CA practices in Wallonia, Belgium, based on a survey of practices in a sample of 48 farmers. Combining the two clustering methods increases the proportion of classified farmers while allowing for the distinction between three CA-types with extreme and salient practices, and two intermediate CA-types comprising farmers whose practices fall between these references. The study reveals that three explanatory factors influence the implementation of CA practices in Wallonia: (i) the proportion of tillage-intensive crops and (ii) temporary grasslands in the crop sequence, and (iii) the organic certification. These factors lead to trade-offs that hinder the three pillars of CA from being fully implemented simultaneously. This new classification method can be replicated in other regions where CA is practiced, by adapting input variables according to context and local knowledge.

Publisher

Springer Science and Business Media LLC

Reference84 articles.

1. Abdi H, Williams LJ (2010) Principal component analysis. WIREs. Comput Stat 2:433–459. https://doi.org/10.1002/wics.101

2. Agreste, Ministère de l’Agriculture, de l’Agroalimentaire et de la Forêt, Secrétariat Général, Service de la Statistique et de la Prospective (2014) Enquête Pratiques culturales 2011 : Principaux résultats. https://agreste.agriculture.gouv.fr/agreste-web/download/publication/publie/Dos21/Dos21.pdf

3. Alkarkhi AFM, Alqaraghuli WAA (2018) Easy statistics for food science with R. Academic Press

4. Alvarez S, Timler CJ, Michalscheck M, Paas W, Descheemaeker K, Tittonell P, Andersson JA, Groot JCJ (2018) Capturing farmdiversity withhypothes is-based typologies: Aninnovative methodological framework for farming system typology development. PLoS ONE 13(5):e0194757. https://doi.org/10.1371/journal.pone.0194757

5. Antier C, Petel T, Baret PV (2019) Quelles agricultures en 2050 ? Comprendre la situation actuelle, Explorer des scénarios pour l’avenir. https://sytra.be/wp-content/uploads/2020/04/UCLouvain-QuellesAgriculturesEn2050-ApercuWeb.pdf

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